ML approaches for omic data analysis

This Programme focuses on the development, implementation, and application of bioinformatics tools for the analysis of large-scale genomic datasets. It aims to facilitate the processing, integration, and interpretation of high-throughput sequencing data, including whole-genome, transcriptome, and epigenome analyses. The Programme encompasses computational approaches for variant discovery, gene expression profiling, network biology, and multi-omics data integration.

DigitalLife aims at bringing together complementary Armenian and German competence of the project partners in three major areas: omics bioinformatics for health with single-cell omics resolution, the establishment of infrastructure for genomic data collection, analysis, and sharing, and the Research School offering a qualification program for young scientists. The research tasks include the development of pathway analysis and machine learning methods and software for single-cell omic data analysis, ...